【摘要】 针对水下传感器网络信息获取过程的特点和压缩感知精确重构原始信号的限制条件,提出一种可调分辨率的水下传感器网络压缩感知重构算法。Sink节点根据获取到的随机观测向量的维度以及给定的分辨率调整策略,计算出重构分辨率,并根据重构分辨率及获取到的节点数据的位置信息处理随机观测向量,构造观测矩阵,最后,采用压缩感知重构算法重构待观测区域的原始物理信息。仿真结果表明,当节点的感知概率较小时,相比于固定分辨率的重构方案,可调分辨率的重构方案能显著提高重构精度。更多还原

【Abstract】 Considering the characteristics in the process of information collection in underwater sensor networks and the restricted requirements of compressed sensing theory,the compressed sensing recovery algorithm with adjustable resolution for underwater sensor networks is proposed in this paper. Firstly,the Sink node computes the reconstruct resolution according to the dimension of the random observed vector and the strategy for adjusting resolution. And then,the random observed vector will be processed,and the observed matrix will be constructed according to the reconstruct resolution and the location information of the node data. Finally,the information of observed area will be reconstructed by compressed sensing recovery algorithm. Simulation results show that the proposed method can improve the reconstruct accuracy in a small sensing probability.更多还原